Tag: modelling

Money has been in use for thousands of years. A large majority of humans seem to be able to function with it. In the realm of psychology, it is referred to as a “secondary reinforcement”, and studies have shown that other animals, especially other apes, can deal with it. Despite all that, I am left with the view that few people actually understand what money is or why it functions as it does. A simple litmus test is to ask “is money a thing of value (worth)?”. True understanding shows that money is not inherently valuable.

The adoption of money, that is to say its use in commerce, did not spread quickly, nor was its evolution without rude surprises for its adherents. As I said earlier, the true need was for some improvement in efficiency and reliability in balancing exchanges of surpluses, or rather tracking the outstanding debts that arose from inequalities in those exchanges. The essential properties needed were as follows:

Scaleability — able to represent amounts of value owed from small to large

Granularity — able to represent amounts to arbitrary precision

Stability — able to retain its identity (the amount owed) over a sufficiently long time

Recognizability — able to not only be recognized by party to whom the debt was owed, but also by the party who owed that debt

An extra bonus for any system that permits such accounting to service exchanges between every pair of parties with surpluses to exchange. This extension would impact all of the essential properties. Getting such a system accepted by a sufficient portion of the population requires a long period of acclimation, with the system needing to evolve over generations of players.

Initially, a party learning to use money is unwilling to accept a lessor item in exchange. Thus, the initial design of money must preserve the illusion that the tokens of money actually embody the worth imagined. Numerous extreme events have shown over and over again that no material can have sufficient value to impart to the tokens the needed value without the value of the material being largely due to its role in producing those tokens (coins). In the more general case, any commodity backing a currency is more valuable as the backing than it can possibly be in all other roles combined. Yet, the illusion, or rather the delusion, of pieces of money having inherent value seems to be a requirement of the initial bootstrapping of monetary systems.

A functioning system of money permits exchanges of surpluses to be distributed over

multiple parties

multiple locations

multiple times

The system rewards its participants by

vastly increasing the opportunity to trade away a surplus before it loses its value

vastly increasing the opportunity to correct shortfalls in needed products

better matching

allowing much greater amounts of specialization

facilitating opportunities for diverse investing

reducing waste or loss via missed opportunities

Those rewards together with the enhanced efficiencies over the long term outweigh the increased risks from counterfeit currency, theft (it too benefits from the efficiency), or simple loss of tokens.

Modern currency is a fiat currency; it has value only in that the powers-that-be dictate that it has value. It seems to be a house of cards, but it cannot fall down because the agencies responsible adjust the supply to match the demand of a vibrant economy (parties cannot shift their trading patterns even as fast as the agencies can withdraw or redeem the currency). We have become dependent on patterns and practices made possible by fiat currency coming-into or going-out-of existence as is needed.

Even more strange is the discovery that money is not a thing, but rather a property of things. We have learned this at a gut or reflex level; we count up our assets by adding together cash, bank accounts, houses, corporate shares, insurance policies, etc; we trade with coins, paper bills, checks, credit cards, eftpos cards, stamps, coupons, etc. Credit cards actually work the reverse of most money systems, they create currency on demand and collapse it on payment — retailers can trade on payments before the customer has actually parted with with the assets.

Game theory is an area of mathematics, where patterns and models from entertainment (games), warfare, politics, economics, and probably other disciplines, were found to be common when stripped of distracting and irrelevant details; this is just as mathematics was formed by so stripping applications from numbers and geometry. Just as an Unrestricted Analyst (UA) would master arithmetic, algebra, geometry, and calculus, so a UA should have some game theory in the tool box.

An informal introduction to game theory can spring out of comparing varying games of entertainment, as such games are already abstract models of problems from other disciplines. One might readily jump to the study of probability and statistics (probStat) on exposure to only one variety of game. To analyze the nature of a difference between two varieties of say either poker or bridge or pinocle, one needs to further abstract things to collect the differences into a unifying category.

Game theory is rather unique. The models of games depend on mainstream mathematics, possibly with probStat and formal logic, but game theory also depends on models of players, complete with formulations of goals and “victory conditions” (how an analyst evaluates outcomes). With models of players comes a dependency on information theory, for players in games differ extremely from the actors in chemistry, physics, electronics, cosmology, etc. Players have intentionality, they do not do things just because they are allowed to; players analyze their situations and act in ways they expect will bring them closer to their goal(s).

Essential to analyzing a player is determining what information the player has, especially how the player views the nature of the game and its goals.

I find from the study of game theory that much benefit (and simplification of analyses) seems to come from dividing into two categories all games and all players. Games are either zero-sum or they are not; players have goals that are self-centric or other-centric. Most games we are aware of (ie. entertainment) are zero-sum to a greater or lessor extent, where zero-sum refers to the net impact on some resource by the actions of players; the net impact is zero in that every gain by one player is counterbalanced by a loss to some other player. Very little of life is really zero-sum!

A player with self-centric goals is generally unconcerned by the actions of other players and victory is to end with more than some arbitrary amount (on some scale in the game). [In real life, a self-centric goal might look like accomplishing more than one’s parents did.] A player with other-centric goals is chiefly concerned with accomplishing more than the other players. [In real life, a player with other-centric goals will generally welcome a loss if it is accompanied by greater losses to the other players; a player with such an other-centric perspective will commonly see situations as zero-sum when they are not.]

This is the beginning of a new thread, economics. I see it as a study of life as seen through a filter, a defining filter. The patterns that show up when looking through that filter are both interesting in the abstract and relevant to directing our subsequent behaviour.

Distilling all human existence down to its most basic shows that our lives are a long series of transactions or conversions. We have a steady increment of time, we get one second for each second, such a trivial and obvious pattern. We have muscles to animate ourselves and have an impact on our surroundings. We have a series of needs, such as: food, drink, shelter, warmth, cooling, comfort, and safety. We use time and our muscles, in fact our whole bodies, to satisfy our needs. Of course, we have learned to use our brains (our minds) to increase our efficiency at getting satisfaction for the our expenditure of time and effort. We have learned to seek the maximum satisfaction for the minimum time and effort; this is the essence of economics.

Life is much more than can be seen through the filter of economics, but all the other pursuits depend on having resources beyond what must be converted (consumed) in order to sufficiently satisfy those needs on which we depend. This leads to a relationship, a pattern, of greater economic efficiency enables greater production of all esthetics, or in other words “economics funds the arts”.

Given human nature and all the people who have ever lived, it seems likely that there have been millions of conspiracies spread unevenly over time, with most of them happenning recently. This means that we cannot issue a blanket dismissal of every claim to have discoverred one, even though it also seems that the majority of such claims are bogus. Thus the scorecard seems litterred with high counts of both false positives (bogus discoveries) and false negatives (undetected conspiracies).

Examining an example may provide illumination. Consider the claim that the moon landing in 1969 was faked. So many of the claims are focussed on the video images and some notion that producing fake images was some how easier than the actual effort could have been. While it is lots of fun to poke holes in these claims, it seems to be only a distraction with no hope of helping the poor fools who peddle them.

A much more complete rebuttal comes from going back to first principles. A conspiracy, by its very nature, is about secrecy, and not just at the time of the event, but forever. Secrecy is so very hard to maintain, and every additional person involved makes it harder. The moon landing event involved tens of thousands of people, regardless of whether it was real or faked; not quite enough to dump the claim yet.

Where the claim completely falls apart is in examining the audience for the event. Yes, the millions of viewers play a role, but most of them are just insignificant viewers. To understand, we need to look at the motivation for both the read event, if it happenned, and the illusion, if we were to suppose it was faked. The ordinary viewers in front of a family TV in the USA are a big part of the numbers but only a tiny part of that motivation. The principle target of the show was the masses of people around the world involved in the political competition between the USA and the International Communists. The family viewers may be easily duped (and are regularly), but the science and engineering communities around the world are much more discerning.

In this analysis, the video is actually relatively unimportant. The crux of the situation is the source of the radio (TV is just a special format of radio) transmission. Radio direction finding is technology that was already well understood in the 1930s. The spheroid shape of the earth, together with witnesses scatterred around the globe, means that faking the transmission would be detected immediately; do not doubt that the USSR would have pointed out such a glaring contradiction if the transmission had not been from the moon.

In summary, lunar landing deniers expect us to accept that tens of thousands of people worked for the USA to produce a fake video (along with the appearance of a functional rocket) that depends on a robot lander to get to the moon intact and operational, carrying either the video or a radio relay, in order to persuade the rest of the world that the USA is superior to USSR, and to reject International Communism. It seems so much more likely that the USA would risk scores of astronaut lives doing the real thing.

Science is a pattern of thought and practice that promotes and is promoted by empowerment. Science is the cataloguing of incidents and the development of models consistent with those incidents. The credibility of science comes through the fundamental principle that all of it exists to permit each and every follower to recreate those incidents on demand and thereby verify the usefulness of those models.

For many people, it is the authority of the speaker that imparts truth to what is said, while for those in the thrall of science it is the speaking of truth that defines an authority. The scientist (and scientifically inclined) sees truth in the models that predict the behavior of the universe, each bit separately and collectively. If such a person cannot benefit by the predictions of outcomes, then the models are forgotten. The models that are shared are those that served best.

Science is different, very different, from mathematics, though both have need for the other. Part of the models used in science are when and how to use pieces of mathematics in producing reliable predictions; science is the connection of mathematics to reality. The objects in mathematics exist there only because they are needed for the consistent behavior of mathematical systems. Truth in mathematics is because it completes and agrees with the rest of mathematics; truth in science is because it predicts the behavior of reality.

Science is a religion or a portion of some religions, in that it requires a belief about the nature of reality. Where it seems to fail to serve all the religious needs of its followers is not explaining the purpose of existence nor proving the correctness of good, although it may provide aid to reason about good and evil.

I am by many measures unusual. My undergraduate degree is a Bachelor’s of Science. This is without further qualifier, such as major. While I have spent decades working as a software engineer, I have come to think of myself as an analyst. I initially thought I was a systems analyst, but I suspect that I am really an unrestricted analyst and have been since years before attending university. I have met a few others who I would also call unrestricted analysts, but we are not common, in fact, not close to common enough, and this is the first time I have used that term to describe us.

I will attempt to explain what I mean by the term unrestricted analyst (UA). When a UA listens to a presentation or engages in a conversation about something, the UA builds light-weight mental models for all the relevant components. A UA then exercises those models to find an easily extracted properties and parameters, especially those that reveal the limits of those models and the corresponding components. Sometimes the exercise of the model spill over and we write down notes and formulae, and give instance to the general description “back of the envelope calculations”. This is similar to the behavior of a systems analyst except that a UA does not limit the practice to any realm or discipline. A UA may be at liberty to decide for his or her self how much detail to incorporate, what degree of precision to use, and even which questions to entertain. For a true UA every situation is potentially one to analyse.

Now for an extreme example. A friend of a friend tried to interest me in a video that purportedly provided indisputable evidence that a top government official played a role in the death of another official. I did not need to see the video to render the evaluation that the video was, at best, worthless. In order for the death of the official, as reported in the media, to have been murder, it would have required far more resources than would have been required to erase that friend-of-a-friend along with the video. Thus, the video was a fraud, the video was a threat to all who got near it, or the implicated official was so far beyond reach that no effort was being expended to suppress the evidence (and this later case could only serve to reveal how impotent we were).